Sarah Tham, Frederick H Koh, Jasmine Ladlad, Koy-Min Chue, Cui-Li Lin, Eng-Kiong Teo, Fung-Joon Foo
{"title":"The imitation game: a review of the use of artificial intelligence in colonoscopy, and endoscopists' perceptions thereof.","authors":"Sarah Tham, Frederick H Koh, Jasmine Ladlad, Koy-Min Chue, Cui-Li Lin, Eng-Kiong Teo, Fung-Joon Foo","doi":"10.3393/ac.2022.00878.0125","DOIUrl":null,"url":null,"abstract":"<p><p>The development of deep learning systems in artificial intelligence (AI) has enabled advances in endoscopy, and AI-aided colonoscopy has recently been ushered into clinical practice as a clinical decision-support tool. This has enabled real-time AI-aided detection of polyps with a higher sensitivity than the average endoscopist, and evidence to support its use has been promising thus far. This review article provides a summary of currently published data relating to AI-aided colonoscopy, discusses current clinical applications, and introduces ongoing research directions. We also explore endoscopists' perceptions and attitudes toward the use of this technology, and discuss factors influencing its uptake in clinical practice.</p>","PeriodicalId":8267,"journal":{"name":"Annals of Coloproctology","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626328/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Coloproctology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3393/ac.2022.00878.0125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/3/10 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The development of deep learning systems in artificial intelligence (AI) has enabled advances in endoscopy, and AI-aided colonoscopy has recently been ushered into clinical practice as a clinical decision-support tool. This has enabled real-time AI-aided detection of polyps with a higher sensitivity than the average endoscopist, and evidence to support its use has been promising thus far. This review article provides a summary of currently published data relating to AI-aided colonoscopy, discusses current clinical applications, and introduces ongoing research directions. We also explore endoscopists' perceptions and attitudes toward the use of this technology, and discuss factors influencing its uptake in clinical practice.
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